




import inspect
import os
import unittest
from dataclasses import dataclass

import torch

from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from accelerate.utils import KwargsHandler





@dataclass
class 					__lowerCamelCase			(       UpperCamelCase__       ):




    """simple docstring"""

    snake_case__   = 0
    snake_case__   = False
    snake_case__   = 3.0






class 					__lowerCamelCase			(       unittest.TestCase       ):




    """simple docstring"""

    def   a (			self	:	Tuple  ) ->			List[str]:
         # If no defaults are changed, `to_kwargs` returns an empty dict.
         self.assertDictEqual(MockClass().to_kwargs()  ,      {}  )
         self.assertDictEqual(MockClass(a=2  ).to_kwargs()  ,      {"a": 2}  )
         self.assertDictEqual(MockClass(a=2  ,      b=SCREAMING_SNAKE_CASE__  ).to_kwargs()  ,      {"a": 2, "b": True}  )
         self.assertDictEqual(MockClass(a=2  ,      c=2.25  ).to_kwargs()  ,      {"a": 2, "c": 2.25}  )


    @require_cuda
    def   a (			self	:	List[Any]  ) ->			str:
         # If no defaults are changed, `to_kwargs` returns an empty dict.
         lowerCAmelCase__            =					GradScalerKwargs(init_scale=1_024  ,      growth_factor=2  )
         AcceleratorState._reset_state()
         lowerCAmelCase__            =					Accelerator(mixed_precision="fp16"  ,      kwargs_handlers=[scaler_handler]  )
         print(accelerator.use_fpaa  )
         lowerCAmelCase__            =					accelerator.scaler

         # Check the kwargs have been applied
         self.assertEqual(scaler._init_scale  ,      1_024.0  )
         self.assertEqual(scaler._growth_factor  ,      2.0  )

         # Check the other values are at the default
         self.assertEqual(scaler._backoff_factor  ,      0.5  )
         self.assertEqual(scaler._growth_interval  ,      2_000  )
         self.assertEqual(scaler._enabled  ,      SCREAMING_SNAKE_CASE__  )


    @require_multi_gpu
    def   a (			self	:	List[str]  ) ->			Optional[int]:
         lowerCAmelCase__            =					["torchrun", f'--nproc_per_node={torch.cuda.device_count()}', inspect.getfile(self.__class__  )]
         execute_subprocess_async(SCREAMING_SNAKE_CASE__  ,      env=os.environ.copy()  )


if __name__ == "__main__":
     UpperCamelCase								=	DistributedDataParallelKwargs(bucket_cap_mb=15, find_unused_parameters=True)
     UpperCamelCase								=	Accelerator(kwargs_handlers=[ddp_scaler])
     UpperCamelCase								=	torch.nn.Linear(100, 200)
     UpperCamelCase								=	accelerator.prepare(model)

     # Check the values changed in kwargs
     UpperCamelCase								=	''
     UpperCamelCase								=	model.bucket_bytes_cap // (1024 * 1024)
     if observed_bucket_cap_map != 15:
          error_msg += F"Kwargs badly passed, should have `15` but found {observed_bucket_cap_map}.\n"
     if model.find_unused_parameters is not True:
          error_msg += F"Kwargs badly passed, should have `True` but found {model.find_unused_parameters}.\n"

     # Check the values of the defaults
     if model.dim != 0:
          error_msg += F"Default value not respected, should have `0` but found {model.dim}.\n"
     if model.broadcast_buffers is not True:
          error_msg += F"Default value not respected, should have `True` but found {model.broadcast_buffers}.\n"
     if model.gradient_as_bucket_view is not False:
          error_msg += F"Default value not respected, should have `False` but found {model.gradient_as_bucket_view}.\n"

     # Raise error at the end to make sure we don't stop at the first failure.
     if len(error_msg) > 0:
          raise ValueError(error_msg)








"""simple docstring"""


import itertools
import math


def        UpperCAmelCase      (					a__ ):





						'''simple docstring'''






						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5     ,      int(math.sqrt(a__ ) + 1 )     ,      6 ):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True


def        UpperCAmelCase      (					):





						'''simple docstring'''






						lowerCAmelCase   :str						=			2
						while True:
												if is_prime(a__ ):
																		yield num
												num += 1


def        UpperCAmelCase      (					a__ = 1_00_01 ):





						'''simple docstring'''






						return next(itertools.islice(prime_generator()     ,      nth - 1     ,      a__ ) )


if __name__ == "__main__":
		print(F"""{solution() = }""")